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George Davey Smith

Other affiliations: Keele University, Western Infirmary, Health Science University  ...read more
Bio: George Davey Smith is an academic researcher from University of Bristol. The author has contributed to research in topics: Population & Mendelian randomization. The author has an hindex of 224, co-authored 2540 publications receiving 248373 citations. Previous affiliations of George Davey Smith include Keele University & Western Infirmary.


Papers
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Journal ArticleDOI
TL;DR: The number of loci associated at genome-wide significance to 7, accounting for a similar proportion of variance as maternal smoking, are extended and highlight genetic links between fetal growth and postnatal growth and metabolism.
Abstract: Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood. Previous genome-wide association studies of birth weight identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes and a second variant, near CCNL1, with no obvious link to adult traits. In an expanded genome-wide association meta-analysis and follow-up study of birth weight (of up to 69,308 individuals of European descent from 43 studies), we have now extended the number of loci associated at genome-wide significance to 7, accounting for a similar proportion of variance as maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes, ADRB1 with adult blood pressure and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism.

309 citations

Journal ArticleDOI
TL;DR: Short sleep over a prolonged period may be associated with an increased risk of mortality: men and women who reported sleeping fewer than 7 h in 24 on two occasions between 4 and 7 years apart, had greater risk of dying from any cause over a 25 year period.

309 citations

Journal ArticleDOI
TL;DR: For instance, the authors found that women who experienced preeclampsia or gestational hypertension in pregnancy had substantially higher levels of body mass index and systolic and diastolic blood pressures and unfavorable lipids compared with other women.
Abstract: Background— Preeclampsia and gestational hypertension are associated with increased risk for cardiovascular disease later in life. We have assessed whether the effect can be attributed to factors that operate in pregnancy or to prepregnancy risk factors that are shared by both disorders. Methods and Results— Longitudinal data from 2 consecutive waves of a Norwegian population-based study (the Nord-Trondelag Health Study [HUNT]) were combined with data from the Medical Birth Registry of Norway. Among 24 865 women who had participated in both HUNT 1 and 2, we indentified 3225 women with a singleton birth between the 2 studies who had standardized measurements of blood pressure, serum lipids, and body mass index. The crude results showed that women who experienced preeclampsia or gestational hypertension in pregnancy had substantially higher levels of body mass index and systolic and diastolic blood pressures and unfavorable lipids compared with other women. However, after adjustment for prepregnancy measure...

307 citations

Journal ArticleDOI
Pim van der Harst1, Weihua Zhang2, Irene Mateo Leach1, Augusto Rendon  +191 moreInstitutions (54)
20 Dec 2012-Nature
TL;DR: A genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals identifies 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10−8, which together explain 4–9% of the phenotypic variance per trait.
Abstract: Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

306 citations

Journal ArticleDOI
TL;DR: The hypothesis that alcohol intake has a marked effect on blood pressure and the risk of hypertension is supported.
Abstract: Background Alcohol has been reported to be a common and modifiable risk factor for hypertension. However, observational studies are subject to confounding by other behavioural and sociodemographic factors, while clinical trials are difficult to implement and have limited follow-up time. Mendelian randomization can provide robust evidence on the nature of this association by use of a common polymorphism in aldehyde dehydrogenase 2 (ALDH2 )a s a surrogate for measuring alcohol consumption. ALDH2 encodes a major enzyme involved in alcohol metabolism. Individuals homozygous for the null variant (*2*2) experience adverse symptoms when drinking alcohol and consequently drink considerably less alcohol than wildtype homozygotes (*1*1) or heterozygotes. We hypothesise that this polymorphism may influence the risk of hypertension by affecting alcohol drinking behaviour.

304 citations


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Journal ArticleDOI
04 Sep 2003-BMJ
TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice? Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis. Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4 Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted? A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …

45,105 citations

Journal ArticleDOI
13 Sep 1997-BMJ
TL;DR: Funnel plots, plots of the trials' effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials.
Abstract: Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure

37,989 citations

Journal ArticleDOI
TL;DR: In this review the usual methods applied in systematic reviews and meta-analyses are outlined, and the most common procedures for combining studies with binary outcomes are described, illustrating how they can be done using Stata commands.

31,656 citations

Journal ArticleDOI
TL;DR: An Explanation and Elaboration of the PRISMA Statement is presented and updated guidelines for the reporting of systematic reviews and meta-analyses are presented.
Abstract: Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

25,711 citations

Journal ArticleDOI
18 Oct 2011-BMJ
TL;DR: The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate.
Abstract: Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate

22,227 citations